Differences In Evapotranspiration Research Articles

Comparative analysis of actual evapotranspiration values estimated by METRIC model using LOCAL data and EEFlux for an irrigated area in Northern Sinaloa, Mexico

Landsat images combined with the METRIC model have been used in applications such as EEFlux to estimate actual evapotranspiration (ETa) in irrigated areas, with uncertainty as to whether the results are sufficiently accurate at local scales. This work compares temporally and spatially ETa estimates using Landsat imagery and the METRIC model with LOCAL measured weather data and EEFlux for an irrigated area in northern Sinaloa, Mexico, from 1995 to 2018. A regression analysis and error metrics such as coefficient of determination (R2), mean absolute error (MAE), root mean square error (RMSE) and slope were used to compare both models. The temporal analysis results confirm that ETa differences are closely related to crop growth and that the daily mean absolute error was 1.17 mm/day. Spatial analysis showed that when using only cropland pixels without non-cropland pixels in EEFlux, the R2 increases from 0.36 to 0.73, and the RMSE decreases from 2.52 to 1.98 mm/day. Therefore, EEFlux should be limited to cropland areas, and it is suggested to exclude Landsat images close to the planting and harvesting season to reduce the differences.

Impact of ET and biomass model choices on economic irrigation water productivity in water-scarce basins

Using Economic Irrigation Water Productivity (EIWP) as an indicator for on-farm irrigation decision-making is of utmost importance in addressing the challenges posed by poor policies in managing agricultural water use, particularly in water-scarce basins. Various modeling systems are available for quantifying crop actual evapotranspiration (ETa) and biomass needed for measuring the economic output obtained from each unit of irrigation water utilized. The difference in ETa and biomass estimates between the modeling systems could translate into a difference in EIWP outcomes, which influences the basin-wide irrigation water management. In this paper we examine the influence of selecting different ETa and biomass models, particularly the hybrid single-source energy balance HSEB, the Global Field-Scale Crop Yield and ET Mapper in Google Earth Engine GYMEE, and FAO’s WaPOR V2, on evaluating EIWP on a basin-wide level. The method includes combining remote sensing and economic data to compare variability in ETa, biomass, and EIWP values derived from HSEB, GYMEE, and WaPOR. The approach is demonstrated with field survey data from the upper hydrologic unit of Lebanon’s largest catchment, the Litani River Basin, in its three productive districts Baalbak, Zahleh, and West Bekaa for the year 2021. Field-scale mean monthly ETa and biomass estimates for all crops, obtained from both models, are very comparable. On a district level, the results reveal a reasonable model agreement for the four crops in the estimation of ETa with moderate to strong correlation (0.75 < r < 0.95). WaPOR consistently produces slightly higher mean ETa values for potato, wheat, and table grapes when compared to HSEB. Both models reasonably agree when estimating biomass for the four crops with high correlation (r > 0.9). Contrary to the ETa results, the GYMEE model consistently estimates slightly higher mean biomass values for all crops compared to WaPOR. The EIWP values produced by both models consistently indicate that potato holds the highest EIWP across all districts, followed by onion, table grapes, and wheat. The mean district HSEB-GYMEE model derived EIWPs are slightly higher than those derived from the WaPOR model for most crops. For EIWP obtained from HSEB-GYMEE, mean EIWP for potato is 12 times higher than that of wheat. As for that obtained from WaPOR, mean EIWP for potato is 10 times higher than that of wheat. The paper establishes a basis for future research on the application of remote sensing models in addressing water-stressed and socioeconomically challenged basins, with the potential to inform strategic irrigation management decisions based on model selection.

Influence of synoptic weather conditions on atmometers on the Delmarva Peninsula, USA

Reference evapotranspiration data from atmometers at three locations on the Delmarva Peninsula (USA) were compared to Penman-Monteith reference evapotranspiration (ETo) data across two growing seasons. Atmometer reference evapotranspiration (ETa) was found to underestimate ETo by 22.8% in 2016 and 30.4% in 2017. Stepwise linear regression was used to examine the relationship between both ET datasets and local meteorological conditions measured by Delaware Environmental Observing System (DEOS) mesonet stations that were co-located with the atmometers. Variability of ETa and ETo are well explained (R2 equal to 0.890 and 0.956, respectively) by a combination of meteorological variables, though the R2 in 2017 (R2 = 0.754) was notably lower than in 2016 (R2 = 0.890). The ET datasets were further examined by partitioning the data into days with similar synoptic conditions using a temporal synoptic index (TSI). Using the TSI results, three dominant synoptic categories were defined during the study period: High Pressure (HP), Southwest Flow (SW), and Cold Fronts (CF). Overall, the similarity between ETa and ETo was greatest on HP days, followed by CF and SW days. This relationship was primarily driven by wind speed, which had the greatest influence on ETa-ETo differences under all synoptic weather patterns. The 2016 growing season consisted of more days with synoptic conditions that are associated with smaller ETa -ETo differences than the 2017 growing season. Thus, changes in synoptic category frequency impact the nature of the ETa-ETo relationship from season to season. This study improves upon previous atmometer comparison studies by associating atmometer correction factors with synoptic weather patterns and descriptions in order to improve the utility of atmometers and remove the need for expensive meteorological equipment to correct atmometer data.

The controlling factors of ecosystem water use efficiency in maize fields under drip and border irrigation systems in Northwest China

The ecosystem water use efficiency (WUEe) is the critical link between water and carbon cycling in the terrestrial ecosystem. The evaluations of the biophysical factors influencing WUEe could reveal mechanisms of controlling WUEe. In order to save water in agriculture, drip irrigation (DI) has been promoted to replace border irrigation (BI) in northwest China. Different irrigation methods will cause differences in evapotranspiration (ETa), gross primary productivity (GPP), and WUEe. Further research is needed to quantify the contribution of each factor to the differences in ETa, GPP, and WUEe. To separate the different factors controlling ETa, GPP, and WUEe variability between DI and border BI, the 4-year data under DI and BI measured by eddy covariance systems were collected and analyzed. To explore the differences in ETa, GPP, and WUEe under different irrigation methods, Penman-Monteith (P-M) model and stomatal conductance-photosynthetic transpiration coupling (SMPT-SB) model complemented by perturbation analysis were employed. The results showed that the 4-year mean evapotranspiration (ETa) decreased by 8% under DI compared with the value under BI, and the mean gross primary productivity (GPP) under DI was 5% higher than the BI. The WUEe under DI was 14% higher than that under BI. The P-M model and the SMPT-SB model agreed well with ETa and GPP measured on daily time scales, providing confidence in their ability to separate the biological and physical controls of ETa, GPP, and WUEe. Based on the two models, the first-order Taylor series expansions of the total ETa, GPP, and WUEe derivatives were applied to the P-M model and SMPT-SB model and compared with measured differences in ETa, GPP, and WUEe. More than 60% of the difference in ETa caused by the two irrigation methods was attributed to variations in the coupled surface resistance, and drip irrigation mainly achieves water saving by reducing soil evaporation. The difference in maize growth due to irrigation methods was the main reason for the differences in GPP. The differences in vapor pressure deficit and the coupled surface resistance caused by irrigation methods were the main factors causing the difference in WUEe. It could be surmised that drip irrigation increased WUEe in maize fields by changing surface resistance, which mainly reduced soil evaporation.

Remotely-sensed water budgets for agriculture in the upper midwestern United States

Process based hydrological models are often the most accurate and comprehensive tools available for answering hydrological questions. However, the resources needed to parameterize and calibrate them can be problematic for small organizations with limited resources or for management questions where emerging problems require rapid investigation. To address this need, this study calculates a simplified monthly water balance using gridded remote sensing actual evapotranspiration (ETa) data and PRISM precipitation data for 223,355 agricultural parcels in Wisconsin totaling 2,966,250 ha of agricultural land. Agricultural management features such as crop rotation and irrigation as well as physical features such as soil drainage and hillslope gradient were compared to identify differences in monthly water budgets. Results showed that Wisconsin was energy limited in most years such that additional precipitation was more likely to suppress ETa. Significant differences were identified with dairy and pasture rotations having the highest annual ETa and the potato/vegetable rotation having the lowest annual ETa rates. Growing season length was identified as a likely predictor of annual ETa. Surprisingly, results also showed that there were no appreciable differences in ETa between rainfed cropland and irrigated cropland. Lastly, results indicated that across all rotations, the months most susceptible to infiltration and runoff were April, May, October, and December. This research demonstrates that cropland management plays a significant role in mitigating or accentuating potential infiltration and runoff relative to variability in precipitation in mesic areas. Without accommodating hydrological variability in mesic, energy-limited areas, water or nutrient conservation policy strategies designed to target average weather conditions may be regularly under-protective or over-restrictive.

The influence of water table depth on evapotranspiration in the Amazon arc of deforestation

Abstract. The Amazon rainforest evapotranspiration (ET) flux provides climate-regulating and moisture-provisioning ecosystem services through a moisture recycling system. The dense complex canopy and deep root system creates an optimum structure to provide large ET fluxes to the atmosphere, forming the source of precipitation. Extensive land use and land cover change (LULCC) from forest to agriculture in the arc of deforestation breaks this moisture recycling system. Crops such as soybean are planted in large homogeneous monocultures and the maximum rooting depth of these crops is far shallower than forest. This difference in rooting depth is key as forests can access deep soil moisture and show no signs of water stress during the dry season, while in contrast crops are highly seasonal with a growing season dependent on rainfall. As access to soil moisture is a limiting factor in vegetation growth, we hypothesised that if crops could access soil moisture, they would undergo less water stress and therefore would have higher evapotranspiration rates than crops which could not access soil moisture. We combined remote-sensing data with modelled groundwater table depth (WTD) to assess whether vegetation in areas with a shallow WTD had higher ET than vegetation in deep WTD areas. We randomly selected areas of forest, savanna, and crop with deep and shallow WTD and examined whether they differ on MODIS Evapotranspiration (ET), Land Surface Temperature (LST), and Enhanced Vegetation Index (EVI), from 2001 to 2012, annually and during transition periods between the wet and dry seasons. As expected, we found no differences in ET, LST, and EVI for forest vegetation between deep and shallow WTD, which because of their deep roots could access water and maintain evapotranspiration for moisture recycling during the entire year. We found significantly higher ET and lower LST in shallow WTD crop areas than in deep WTD during the dry season transition, suggesting that crops in deep WTD undergo higher water stress than crops in shallow WTD areas. The differences found between crop in deep and shallow WTD, however, are of low significance with regards to the moisture recycling system, as the difference resulting from conversion of forest to crop has an overwhelming influence (ET in forest is ≈2 mm d−1 higher than that in crops) and has the strongest impact on energy balance and ET. However, access to water during the transition between wet and dry seasons may positively influence growing season length in crop areas.

Assessment of the indirect impact of wildfire (severity) on actual evapotranspiration in eucalyptus forest based on the surface energy balance estimated from remote-sensing techniques

ABSTRACTWildfires have a strong impact on the environment, changing its structure, soil properties, and microclimate and subsequently its water cycle with implications on the surface energy fluxes. Persisting droughts and catastrophic forest fires initiated this case study of pure eucalyptus stands in north-central Portugal. Although many studies have investigated changes in actual evapotranspiration (ETa), surface energy flux patterns, and the related physical parameters, only a few concentrated on the fire-driven changes in pure eucalyptus stands in the Mediterranean climate. This study aims to understand the consequences of wildfires on the water cycle, namely the ETa, and the surface energy heat fluxes by applying a simplified two-source energy balance model in combination with medium-resolution imagery (Landsat 8). A total of 21 different burnt locations were evaluated, which burned between 2011 and 2013. Estimated surface energy fluxes and daily ETa were compared to nearby control sites (unburnt) during satellite overpass for the time after the fire (2013–2015). The fire scars were classified into their burn severity, using the differenced Normalized Burn Ratio. The absolute difference of ETa ( ETa) between unburnt and burnt locations was used to identify fire-driven changes in magnitude and its evolution over time. Our results show that for the unburnt stands, the contributions to the total latent heat flux were around 80% from the canopy and 20% from the soil, while for the burnt site the contributions were around 30% (canopy) and 70% (soil) shortly after the fire. Inter-annually, the difference in ETa increased during the rainy season, which was related to the epicormic shooting, the fast regrowth rate of foliage, and the abundance of water. Generally, smaller differences in ETa were related to the severity classification and stand properties (i.e. tree species and soil characteristics). Two to three years after the fire events, ETa became non-significant for all severity classes, leading to an impact on the total water cycle smaller in comparison to other post-fire studies.

Using weather forecast data for irrigation scheduling under semi-arid conditions

A new methodology based on the use of weather forecast data from freely and easily accessible online information for determining irrigation scheduling has been developed. Firstly, reference evapotranspiration (ETo) was determined with a user-friendly procedure that does not require previous local calibration, knowledge of data acquisition or processing, or a nearby weather station. The comparison of ETo based on short-term (same-day) and long-term (6-day-ahead) weather forecast data with measured data for 50 locations in southern Spain during 2013–2014 season indicated that differences in ETo were relatively low with root-mean-square error (RMSE) equal to 0.65 and 0.76 mm d−1, respectively. The procedure was tested for a wide range of weather conditions in the development of irrigation schedules and yield simulations for maize crop during 2013–2014 season. Irrigation water depths provided by irrigation schedules based on ETo obtained from daily and weekly forecasts and from measured data showed differences of around 1.5 and 0.9 %, respectively. Likewise, yield simulation with irrigation scheduling based on forecast and measured data provided equal averaged values, with a relative RMSE of below 5 %. This similarity of irrigation scheduling and yield estimation based on forecast and measured data has proved the optimal performance of the proposed approach.

Actual evapotranspiration and precipitation measured by lysimeters: a comparison with eddy covariance and tipping bucket

Abstract. This study compares actual evapotranspiration (ETa) measurements by a set of six weighable lysimeters, ETa estimates obtained with the eddy covariance (EC) method, and evapotranspiration calculated with the full-form Penman–Monteith equation (ETPM) for the Rollesbroich site in the Eifel (western Germany). The comparison of ETa measured by EC (including correction of the energy balance deficit) and by lysimeters is rarely reported in the literature and allows more insight into the performance of both methods. An evaluation of ETa for the two methods for the year 2012 shows a good agreement with a total difference of 3.8% (19 mm) between the ETa estimates. The highest agreement and smallest relative differences (&lt; 8%) on a monthly basis between both methods are found in summer. ETa was close to ETPM, indicating that ET was energy limited and not limited by water availability. ETa differences between lysimeter and EC were mainly related to differences in grass height caused by harvest and the EC footprint. The lysimeter data were also used to estimate precipitation amounts in combination with a filter algorithm for the high-precision lysimeters recently introduced by Peters et al. (2014). The estimated precipitation amounts from the lysimeter data differ significantly from precipitation amounts recorded with a standard rain gauge at the Rollesbroich test site. For the complete year 2012 the lysimeter records show a 16 % higher precipitation amount than the tipping bucket. After a correction of the tipping bucket measurements by the method of Richter (1995) this amount was reduced to 3%. With the help of an on-site camera the precipitation measurements of the lysimeters were analyzed in more detail. It was found that the lysimeters record more precipitation than the tipping bucket, in part related to the detection of rime and dew, which contribute 17% to the yearly difference between both methods. In addition, fog and drizzle explain an additional 5.5% of the total difference. Larger differences are also recorded for snow and sleet situations. During snowfall, the tipping bucket device underestimated precipitation severely, and these situations contributed also 7.9% to the total difference. However, 36% of the total yearly difference was associated with snow cover without apparent snowfall, and under these conditions snow bridges and snow drift seem to explain the strong overestimation of precipitation by the lysimeter. The remaining precipitation difference (about 33%) could not be explained and did not show a clear relation to wind speed. The variation of the individual lysimeters devices compared to the lysimeter mean are small, showing variations up to 3% for precipitation and 8% for evapotranspiration.